Methoden vergelijken

	Foster-Greer-Thorbecke Index	Poverty Dominance Analysis
Vakgebied	Economie	Economie
Familie	Process / pipeline	Process / pipeline
Jaar van ontstaan	1984	1987
Grondlegger	James Foster, Joel Greer & Erik Thorbecke	Anthony Atkinson (1987); James Foster & Anthony Shorrocks (1988)
Type	Parametric class of poverty measures	Robust distributional ordering
Oorspronkelijke bron	Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761–766.	Atkinson, A. B. (1987). On the measurement of poverty. Econometrica, 55(4), 749–764.
Aliassen	FGT Index, FGT Poverty Measures, P-alpha Poverty Index, Foster-Greer-Thorbecke Poverty Measure	Stochastic Dominance Analysis, Poverty Orderings, TIP Curve Analysis, First- and Second-Order Poverty Dominance
Verwant	4	3
Samenvatting	The Foster-Greer-Thorbecke (FGT) index is a parametric class of poverty measures introduced by James Foster, Joel Greer, and Erik Thorbecke in 1984 that became the workhorse of applied poverty analysis. A single parameter alpha tunes how much weight the measure places on the depth and distribution of poverty: alpha = 0 gives the headcount ratio (the share of people below the poverty line), alpha = 1 gives the poverty gap (the average normalized shortfall), and alpha = 2 gives poverty severity (which weights larger shortfalls more heavily). Its defining virtue is additive decomposability — total poverty is the population-weighted sum of subgroup poverty — which makes it ideal for profiling poverty across regions, sectors, and demographic groups.	Poverty dominance analysis asks whether one distribution has unambiguously less poverty than another for a whole class of poverty measures and a whole range of poverty lines, rather than for a single index and a single line. Building on Anthony Atkinson's 1987 stochastic-dominance treatment of poverty and the Foster-Shorrocks 1988 poverty-orderings results, it compares cumulative distribution functions (poverty incidence curves) and their successive integrals (poverty deficit and severity curves). When the curve for one distribution lies everywhere below another, that distribution has less poverty for every measure in a corresponding class and every line in the range — a robust conclusion immune to the index-and-line arbitrariness that bedevils single-number comparisons.